Out of CPU cycles and in need to do science? No problem!

After the bad experience of spending money in clusters and grids and then spending more time doing maintenance, hack-proofing and installing stuff than science, maybe it is the time to rethink how massive distributed evolutionary computation should be done. Nowadays there are lots of free or use-based resources that can be tapped for doing volunteer-based evolutionary algorithms. That is way my last keynote and tutorial have dealt with that: the IDC Keynote, Low or No Cost Evolutionary computation, which you can access here in Heroku, puts the money where its mouth is: talking and doing volunteer-based evolutionary computing at the same time. The PPSN tutorial, Low or no cost distributed evolutionary computation, touched on the same topic, only longer and with more enphasis on tools.
So finally it is just a matter of a little Javascript and using free cloud resources and you can have your very own massive distributed experiment. Whose results will be published soon enough.

CFP for EvoGAMES 2015

jjmerelo:

Are you into games and computational intelligence? Submit your paper to this conference track, deadline in a month.

Originally posted on The EvoGAMES blog:

The deadline for EvoGAMES 2015 is approaching: 15 November.

Please, prepare ASAP your (excellent :D) contribution to the edition of this year, for two main reasons: first Evo* will be held in the beautiful city of Copenhagen (Denmark); and second, we are working hard to join a special issue in a very good JCR journal.

Thus, the selected papers will be proposed to be included in it, after an extension/improvement phase, of course. ;)

The main topics are (not limited to):

  • Computational Intelligence in video games
  • Intelligent avatars and new forms of player interaction
  • Player experience measurement and optimization
  • Procedural content generation
  • Human-like artificial adversaries and emotion modelling
  • Authentic movement, believable multi-agent control
  • Experimental methods for gameplay evaluation
  • Evolutionary testing and debugging of games
  • Adaptive and interactive narrative
  • Games related to social, economic, and financial simulations
  • Adaptive educational, serious and/or social games
  • General game intelligence (e.g. general purpose…

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[Paper] My life as a sim: evolving unique and engaging life stories using virtual worlds

Our latest publication My life as a sim: evolving unique and engaging life stories using virtual worlds, using our framework MADE (created by @rubenhek), has been published in the ALIFE 2014 conference. The abstract:

Stories are not only painfully weaved by crafty writers in the solitude of their studios; they also have to be produced massively for non-player characters in the video game industry or tailored to particular tastes in personalized stories. However, the creation of fictional stories is a very complex task that usually implies a creative process where the author has to combine characters, conflicts and backstories to create an engaging narrative. This work describes a general methodology to generate cohesive and coherent backstories where desired archetypes (universally accepted literary symbols) can emerge in complex stochastic systems. This methodology supports the modeling and parametrization of the agents, the environment where they will live and the desired literary setting. The use of a Genetic Algorithm (GA) is proposed to establish the parameter configuration that will lead to backstories that best fit the setting. Information extracted from a simulation can then be used to create the literary work. To demonstrate the adequacy of the methodology, we perform an implementation using a specific multi-agent system and evaluate the results, testing with three different literary settings.

Check out the presentation by @jjmerelo at http://jj.github.io/alife14-made/#/home. You can download the proceedings of the conference (CC license), or download the paper draft.

More information is available on the project page.

Tenemos el segundo bot más humano DEL MUNDO…

…jugando a Unreal Tournament 2004. :D

José L. Jiménez, estudiante de informática de la Universidad de Málaga, dirigido por Antonio Fernández Leiva y por mí ha creado un bot, llamado NizorBot, a partir del ExpertBot que hicieron Francisco Aisa y Ricardo Caballero, que ha obtenido el segundo puesto (considerando la humanidad (humanness) del mismo) en el BotPrize 2014, celebrado dentro del CIG 2014.

Human or Bot competition (BotPrize)

Resultados de la competición BotPrize 2014 (primeros puestos)

La competición se basa en un Test de Turing que los bots deben pasar frente a jueces humanos. Éstos se enfrentarán a los bots en combates (Deathmatch) dentro del juego Unreal Tournament 2004. Durante dichos combates (en varias tandas), los jueces marcarán a cada uno de sus rivales como humano o bot en base a su criterio sobre el comportamiento que observen en el jugador.

Además, este año se ha añadido la presencia de un gran número de jueces off-line, es decir, ‘fuera del juego’, que visualizan los enfrentamientos y deciden también qué jugadores son humanos y cuáles no.

Esto le da más valor al resultado que otros años, ya que estos jueces cuentan con un punto de vista ‘menos limitado’ que los participantes en el juego.

El bot ha sido implementado mediante algoritmos evolutivos interactivos, en los que un controlador humano interviene cada cierto tiempo en dos sentidos:

  • Ajustando parámetros del algoritmo (controlador experto en el algoritmo)
  • Respondiendo a cuestiones sobre el jugador y el juego (controlador experto en el juego).

En ambos casos, el desarrollo del algoritmo (su ejecución) se ve afectado y dirigido por este controlador, lo que hace que el bot evolucione de una forma más acorde con lo que éste espera. En este caso, para comportarse de la manera más humana posible.

José está en proceso de escritura de su Proyecto Fin de Carrera y, a continuación, los tres trabajaremos en un artículo describiendo todo el proceso.

¡Estad atentos! :D

Aplicación de Programación Genética para la generación de bots del RTS Planet Wars en CoSECiVi 2014

Este trabajo se publicó dentro del Primer Congreso de la Sociedad Española para las Ciencias del Videojuego (CoSECIVI), que se celebró en conjunción con el Gamelab 2014 en Barcelona.

En él se presentó el artículo titulado “Designing Competitive Bots for a Real Time Strategy Game using Genetic Programming”, cuyo resumen (en inglés) es:

The design of the Artificial Intelligence (AI) engine for an autonomous agent (bot) in a game is always a difficult task mainly done by an expert human player, who has to transform his/her knowledge into a behavioural engine. This paper presents an approach for conducting this task by means of Genetic Programming (GP) application. This algorithm is applied to design decision trees to be used as bot’s AI in 1 vs 1 battles inside the RTS game Planet Wars. Using this method it is possible to create rule-based systems defining decisions and actions, in an automatic way, completely different from a human designer doing them from scratch. These rules will be optimised along the algorithm run, considering the bot’s performance during evaluation matches. As GP can generate and evolve behavioural rules not taken into account by an expert, the obtained bots could perform better than human-defined ones. Due to the difficulties when applying Computational Intelligence techniques in the videogames scope, such as noise factor in the evaluation functions, three different fitness approaches have been implemented and tested in this work. Two of them try to minimize this factor by considering additional dynamic information about the evaluation matches, rather than just the final result (the winner), as the other function does.
In order to prove them, the best obtained agents have been compared with a previous bot, created by an expert player (from scratch) and then
optimised by means of Genetic Algorithms. The experiments show that the three used fitness functions generate bots that outperform the optimized human-defined one, being the area-based fitness function the one that produces better results.

La presentación del artículo se puede ver aquí:

El artículo se puede encontrar en: http://gaia.fdi.ucm.es/sites/cosecivi14/es/papers/24.pdf

Esperamos que os guste.

Y que nos citéis. :D

[Paper] A Methodology to Develop Service Oriented Evolutionary Algorithms

fergunet:

Paper about our methodology for service oriented EAs

Originally posted on OSGiLiath Evolutionary Framework:

Our paper A Methodology to Develop Service Oriented Evolutionary Algorithms has been published in the proceedings of the 8th International Symposium on Intelligent Distributed Computing – IDC’2014. This paper is a resume of the SOA-EA methodology, one of the chapters of my thesis (available here). The presentation, made by JJ Merelo, is quite cool:

http://jj.github.io/pres-idc-2014/index.html#/home

The abstract:

This paper proposes a methodology to design and implement Evolutionary Algorithms using the Service Oriented Architecture paradigm. This paradigm allows to deal with some of the shortcomings in the Evolutionary Algorithms area, facilitating the development, integration, standardization of services that conform a evolutionary algorithm, and, besides, the dynamic alteration of those elements in runtime.
A four-step methodology to design services for Evolutionary Algorithms is presented: identification, specification, implementation and deployment. Also, as an example of application of this methodology, an adaptive algorithm is developed.

You can download the paper draft from…

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Free access to paper accepted at GECCO’14

During 1 month, papers accepted at GECCO1’4 will be freely available. Thus, you can get and read our papers:

  • “Assessing different architectures for evolutionary algorithms in javascript” by Juan Julián Merelo, Pedro Castillo, Antonio Mora, Anna I. Esparcia-Alcázar, Víctor M. Rivas Santos (doi 10.1145/2598394.2598460) at http://goo.gl/jqLud5
  • NodEO, a multi-paradigm distributed evolutionary algorithm platform in JavaScript” by Juan-Julián Merelo, Pedro Castillo, Antonio Mora, Anna Esparcia-Alcázar, Víctor Rivas-Santos (doi:10.1145/2598394.2605688) at http://goo.gl/eFmv1T
  • “Enforcing corporate security policies via computational intelligence techniques” by Antonio M. Mora, Paloma De las Cuevas, Juan Julián Merelo, Sergio Zamarripa, Anna I. Esparcia-Alcázar (doi: 10.1145/2598394.2605438) at http://goo.gl/33gWES
  • A methodology for designing emergent literary backstories on non-player characters using genetic algorithms”, by Rubén Héctor García-Ortega, Pablo García-Sánchez, Antonio Miguel Mora, Juan Julián Merelo (doi: 10.1145/2598394.2598482) at http://goo.gl/9CEcMc

Enjoy!